Collision avoidance

About: Collision avoidance is a research topic. Over the lifetime, 8014 publications have been published within this topic receiving 111414 citations.

Collision-Free Multi-UAV Optimal Path Planning and Cooperative Control for Tactical Applications

Abstract: Stemming from previous work that addressed the optimal path planning of an unmanned aerial vehicle (UAV) in obstacle-rich environments, this paper demonstrates the approach’s scalability to that of a multi-UAV application. The proposed concept, based on optimal control techniques and pseudospectral methods, offers the improved system flexibility and autonomy demanded by UAV tactical missions in urban areas. As demonstrated, employing optimal control methods for path planning problems provides a simplistic yet powerful capability of flight trajectory optimization that includes simultaneous collision avoidance between vehicles and terrain obstacles. Departing from traditional techniques that harbor non-optimal architectures, the employed method facilitates real-time, onboard computations that may potentially improve overall system performance. Recent developments in the field of optimal control theory point at an emerging paradigm shift that may involve less dependency on the typical inner-loop control. Extending these developments, this paper provides not only a fresh perspective, but also illustrates a viable technique for efficiently generating maneuvering flight trajectories for single vehicles or multiple vehicle sorties.

Collision avoidance systems in air and maritime traffic

Abstract: In each transport mode, collisions between vehicles are one of the major operational risks. In maritime traffic collisions and groundings is the category with the highest frequency of all accidents. Although new navigational equipment, often combined with enhanced computer-based systems, is installed on ships’ bridges, the number of collisions is still at a high level. The equivalent of ship collisions in air traffic is the mid-air collision. Compared to the maritime accident rate, mid-air collisions are very rare. In this paper we investigate the onboard collision avoidance process by focusing on technical support systems with implemented alerts to support the human operator. Empirical field studies have been undertaken to analyse the situation regarding the occurrence and handling of alerts onboard seagoing vessels. Especially with respect to collision avoidance alarms, the situation was found to be unsatisfactory. The algorithms in use are based on fixed static limit values and little selected informat...

Collision protection system for automotive vehicles comprises measurement sensors, a data processing system and means for controlling a vehicle to prevent a collision

Abstract: The collision protection system calculates the separation distances between a vehicle and an obstacles in the surroundings are measured and used to calculate the available driving space. Additional values relating to the actual vehicle movement, such as speed, direction, deceleration, etc., are measured and used in conjunction with the vehicle dimensions to calculate the required space in the forwards direction. This is compared with the available space and if necessary collision avoidance measures are implemented. An Independent claim is made for a device for avoiding collisions of a motor vehicle with measurement means, data processing means and means for controlling the vehicle to prevent a collision.

Automatic collision avoidance for manually tele-operated unmanned aerial vehicles

Abstract: In this paper we present an approach that aids the human operator of unmanned aerial vehicles by automatically performing collision avoidance with obstacles in the environment so that the operator can focus on the global direction of motion of the vehicle. As opposed to systems that override operator control as a last resort in order to avoid collisions (such as those found in modern automobiles), our approach is designed such that the operator can rely on the automatic collision avoidance, enabling intuitive and safe operator control of vehicles that may otherwise be difficult to control. Our approach continually extrapolates the future flight path of the vehicle given the current operator control input. If an imminent collision is predicted our algorithm will override the operator’s control input with the nearest control input that will actually let the vehicle avoid collisions with obstacles. This ensures safe flight while simultaneously maintaining the intent of the human operator as closely as possible. We successfully implemented our approach on a physical quadrotor system in a laboratory environment. In all experiments the human operator failed to crash the vehicle into floors, walls, ceilings, or obstacles, even when deliberately attempting to do so.

A new safe lane-change trajectory model and collision avoidance control method for automatic driving vehicles

Abstract: Lane change maneuvers, are important contributors to road traffic accidents on highway. In this paper, we propose a new safe lane change trajectory model and collision avoidance control method for Society of Automotive Engineers (SAE)-level 2 automatic driving vehicles. First, a Gaussian distribution is used to describe the new trajectory model that uses pure steering and combined braking. According to regional and progressive states, a new safe lane change meaning is defined. Second, we design a new four-level automatic driving mode and an effective decision mechanism that considers safety and ergonomics. Moreover, a new trajectory tracking controller combined with a decision mechanism was designed using feedback linearization, verified using typical lane-change scenarios. Finally, based on a physical simulation platform, PreScan, the hardware-in-the-loop simulation result demonstrate the feasibility and effectiveness of our method. This paper provides a valuable reference on an expert and intelligent system methodology for automatic driving vehicles, which will be helpful for improving highway traffic safety and efficiency.